DatastatResearch

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Training Course on M »

INTRODUCTION

The interest for information on the effect of approaches, projects and interventions on food and nutrition security is growing rapidly. The public sector, including the civil society and governments, frequently monitor data on food and nutrition in order to determine the existing trends and conditions, and the impact of interventions and policies.

International agencies, NGOs, governments and other agencies carry out monitoring, evaluation, and impact assessments regularly. With regard to this fact, this course lays emphasis on the need to carefully select the right set of indicators when designing information support systems at various administrative levels as well as the skills required for the analysis and interpretation of collected data.

The course adopts and interactive training approach and provides participants the chance to learn from each other as well as from the expert facilitators.

WHO SHOULD ATTEND

This course is relevant to managers, professionals, team members or consultants.

DURATION

5 days

COURSE OBJECTIVES

Understand the role of food security and nutrition for attaining the MDGs

Gain fresh insights on the values of participatory & learning-oriented design, monitoring, and evaluation with regard to food security and nutrition.

To strengthen your competence in designing an M&E-system

Have clear ideas for the improvement of M&E systems and impact assessment for food security and nutrition.

COURSE CONTENT

Introduction

Food Security frameworks and concepts

M& E Fundamentals

Data sources collection and use

Defining a good M&E system

Identifying the challenges that face Monitoring and evaluation in the Food Security and Nutrition sector

Including M&E in food security program design

M&E Frameworks

M&E Plans

Participatory M&E systems

M&E Frameworks

Developing and operationalizing M&E frameworks

Linking M&E frameworks to indicators

M&E Frameworks basics for Food Security and other programs

M&E in Food Security and Nutrition context

Monitoring results and impacts using a logical framework

Gender M&E

Exploring gender in M&E plans

Gender considerations for data collection

Introduction to M&E in Gender and Food Security

Selecting indicators to measure gender-related outputs and outcomes

Prioritizing gender in M&E plans

Step by Step approaches to M&E

Agree on and design core documents to setup an M&E system

Agree on field monitoring data collection and management process

Agree on Monitoring data analysis process

Agree on process for monitoring data utilization and reporting

Agree on process of evaluation management

Agree on the principles and purpose of the project M&E system

Establish project M&E system

Review and revise M&E plans based on progress

Interpreting and Communicating results for M&E

Communication and reporting for M&E

Contemporarily methods of dissemination

Data collection, management and data quality

Data collection methods (quantitative and qualitative)

Data collection versus data analysis

Data quality and data management

Data quality dimensions

Double counting

Functional areas of data management systems

Increasing questionnaires response rates

M&E field trips

ICT tools for data collection, monitoring and evaluation in food security and nutrition

Case study

Dashboards; data management analytics, and stakeholders access

Data collection implementation models

ICT tool for Data processing

Key choice of application to collect data in rural areas

Using Mobile phones for data collection

Data demand for food security and nutrition programs

Data demand

Data use frameworks and key concepts

Information availability

Information use

Introduction to Data analysis Food Security and Nutrition Programs

Basic analysis

Data analysis key concepts

Introduction

Types of variables

Summarizing data

Graphs and charts for continuous variables

Graphs and charts for dichotomous and categorical variables

Graphs and charts for ordinal variables

Numerical summaries for discrete variables

Tables for categorical variables

Tables for dichotomous variables

Tables for ordinal variables

Tabulations for summary statistics for continuous variables

Introduction to qualitative data Analysis

Coding the data

Introduction to qualitative data analysis software (NVivo)

Organizing your data

Planning for qualitative data analysis

Reviewing the data

Quantitative data Analysis

Basics for statistical analysis

Choosing the correct statistical test

Comparison of Data analysis packages

Confidence intervals

Hypothesis testing

Hypothesis testing versus confidence intervals

Interpreting the data

Planning for qualitative data analysis

Testing for normality of data

Tests of statistical significance

Assessing Programme Impact on Food Security

Impact Assessment in Programme Design

Introduction to Impact Assessment

Programme Design Implications

Methods and Approaches for Assessing Impact

Overview of Methods and Approaches

Qualitative Methods

Quantitative Methods: Household Surveys

Quantitative Methods: Secondary Data

Selecting Methods and Approaches

METHODOLOGY

The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.

The type of research design, philosophical assumptions, and methodologies used by a researcher are key determinants of the outcome and the validity of a particular research. In order to carry out and evaluate any research

The type of research design, philosophical assumptions, and methodologies used by a researcher are key determinants of the outcome and the validity of a particular research. In order to carry out and evaluate any research

The type of research design, philosophical assumptions, and methodologies used by a researcher are key determinants of the outcome and the validity of a particular research. In order to carry out and evaluate any research